July 11, 2019 — Jacob Wells, Technical Specialist, European Sales
With the recent announcement of the all-new Raspberry Pi 4, we are proud to announce that our latest development, Version 12 of Mathematica and the Wolfram Language, is available for you to use when you get your hands on the Raspberry Pi 4.
Mathematica 12 is a major milestone in our journey that has spanned 30 years, significantly extending the reach of Mathematica and introducing a whole array of new features, including significant expansion of numerical, mathematic and geometric computation, audio and signal processing, text and language processing, machine learning, neural networks and much more. Version 12 gives Mathematica users new levels of power and effectiveness. With thousands of different updates across the system, and 278 new functions in 103 areas, there is so much to explore.
July 2, 2019 — Jon McLoone, Director, Technical Communication & Strategy
This week, I won some money applying a mathematical strategy to a completely unpredictable gambling game. But before I explain how, I need to give some background on last-mover advantage.
Some time ago, I briefly considered doing some analysis of the dice game Yahtzee. But I was put off by the discovery that several papers (including this one) had already enumerated the entire game state graph to create a strategy for maximizing the expected value of the score (which is 254.59).
However, maximizing the expected value of the score only solves the solo Yahtzee game. In a competitive game, and in many other games, we are not actually trying to maximize our score—we are trying to win, and these are not always the same thing.
Easter Eggs in Plain Sight, Climate Change Challenges and Knitted Images: Wolfram Community Highlights
June 25, 2019 — Chapin Langenheim, Editorial Project Coordinator, Project Management
Wolfram Community is our favorite, continually growing forum to share and show support for projects using the Wolfram Language, connect with other Mathematica aficionados and find solutions for coding questions. It’s also a great platform for sharing computational innovations that can benefit your local community—or beyond. We’ve collected some of the exciting ways Wolfram Community members have been giving back through Wolfram technology—check them out!
June 20, 2019 — Brian Wood, Lead Technical Marketing Writer, Document and Media Systems
Mapping an Ancient Empire
Geocomputation is an indispensable modern tool for analyzing and viewing large-scale data such as population demographics, natural features and political borders. And if you’ve read some of my other posts, you can probably tell that I like working with maps. Recently, a Wolfram Community member asked:
“How do I make an interactive map of the
Byzantine Empire through the years?”
To figure out a solution, we’ll tap into the Wolfram Knowledgebase for some historical entities, as well as some of the high-level geocomputation and visualizations of the Wolfram Language. Once we’ve created our brand-new function, we’ll submit it to the Wolfram Function Repository for anyone to use.
June 11, 2019 — Stephen Wolfram
What the Wolfram Language Makes Possible
We’re on an exciting path these days with the Wolfram Language. Just three weeks ago we launched the Free Wolfram Engine for Developers to help people integrate the Wolfram Language into large-scale software projects. Now, today, we’re launching the Wolfram Function Repository to provide an organized platform for functions that are built to extend the Wolfram Language—and we’re opening up the Function Repository for anyone to contribute.
The Wolfram Function Repository is something that’s made possible by the unique nature of the Wolfram Language as not just a programming language, but a full-scale computational language. In a traditional programming language, adding significant new functionality typically involves building whole libraries, which may or may not work together. But in the Wolfram Language, there’s so much already built into the language that it’s possible to add significant functionality just by introducing individual new functions—which can immediately integrate into the coherent design of the whole language.
To get it started, we’ve already got 532 functions in the Wolfram Function Repository, in 26 categories:
June 6, 2019 — Alec Shedelbower, Kernel Developer, Algorithms R&D
You know what’s harder than learning the piano? Learning the piano without a piano, and without any knowledge of music theory. For me, acquiring a real piano was out of the question; I had neither the funds nor space in my small college apartment. So naturally, it looked like I would have to build one myself—digitally, of course. And luckily, I had Mathematica, Unity and a few hours to spare. Because working in Unity is incredibly quick and efficient with the Wolfram Language and UnityLink, I’ve created a playable section of piano, and even learned a bit of music theory in the process.
May 28, 2019 — Daniel Lichtblau, Symbolic Algorithms Developer, Algorithms R&D
Several Months Ago…
I wrote a blog post about the disputed Federalist Papers. These were the 12 essays (out of a total of 85) with authorship claimed by both Alexander Hamilton and James Madison. Ever since the landmark statistical study by Mosteller and Wallace published in 1963, the consensus opinion has been that all 12 were written by Madison (the Adair article of 1944, which also takes this position, discusses the long history of competing authorship claims for these essays). The field of work that gave rise to the methods used often goes by the name of “stylometry,” and it lies behind most methods for determining authorship from text alone (that is to say, in the absence of other information such as a physical typewritten or handwritten note). In the case of the disputed essays, the pool size, at just two, is as small as can be. Even so, these essays have been regarded as difficult for authorship attribution due to many statistical similarities in style shared by Hamilton and Madison.
May 23, 2019 — Brian Wood, Lead Technical Marketing Writer, Document and Media Systems
Just as Wolfram was doing AI before it was cool, so have we been doing data science since before it was mainstream. A prime example is the creation of Wolfram|Alpha—a massive project that involved engineering, modeling, analyzing, visualizing and interfacing with terabytes of data, developing a natural language interface, and deploying results in a sensible way. Wolfram|Alpha itself is a tool for doing data science, and its continued success is largely because of the underlying strategy we used to build it: a multiparadigm approach driven by natural curiosity, exploring all kinds of data, using advanced methods from a range of areas and automating as much as possible.
Any approach to data science can only be as effective as the computational tools driving it; luckily for us, we had the Wolfram Language at our disposal. Leveraging its universal symbolic representation, high-level automation and human readability—as well as its broad range of built-in computation, knowledge and interfaces—streamlined our process to help bring Wolfram|Alpha to fruition. In this post, I’ll discuss some key tenets of the multiparadigm approach, then demonstrate how they combine with the computational intelligence of the Wolfram Language to make the ideal workflow for not only discovering and presenting insights from your data, but also for creating scalable, reusable applications that optimize your data science processes.
May 21, 2019 — Stephen Wolfram
Why Aren’t You Using Our Technology?
It happens far too often. I’ll be talking to a software developer, and they’ll be saying how great they think our technology is, and how it helped them so much in school, or in doing R&D. But then I’ll ask them, “So, are you using Wolfram Language and its computational intelligence in your production software system?” Sometimes the answer is yes. But too often, there’s an awkward silence, and then they’ll say, “Well, no. Could I?”
I want to make sure the answer to this can always be: “Yes, it’s easy!” And to help achieve that, we’re releasing today the Free Wolfram Engine for Developers. It’s a full engine for the Wolfram Language, that can be deployed on any system—and called from programs, languages, web servers, or anything.
The Wolfram Engine is the heart of all our products. It’s what implements the Wolfram Language, with all its computational intelligence, algorithms, knowledgebase, and so on. It’s what powers our desktop products (including Mathematica), as well as our cloud platform. It’s what’s inside Wolfram|Alpha—as well as an increasing number of major production systems out in the world. And as of today, we’re making it available for anyone to download, for free, to use in their software development projects.
May 18, 2019 — Stephen Wolfram
The Wolfram|Alpha Story
Today it’s 10 years since we launched Wolfram|Alpha. At some level, Wolfram|Alpha is a never-ending project. But it’s had a great first 10 years. It was a unique and surprising achievement when it first arrived, and over its first decade it’s become ever stronger and more unique. It’s found its way into more and more of the fabric of the computational world, both realizing some of the long-term aspirations of artificial intelligence, and defining new directions for what one can expect to be possible. Oh, and by now, a significant fraction of a billion people have used it. And we’ve been able to keep it private and independent, and its main website has stayed free and without external advertising.